System and method for adaptive extension of command and control (c2) backhaul network for unmanned aircraft systems (uas)

ABSTRACT

A system and method for adaptive extension of a command and control (C2) backhaul network for unmanned aircraft systems (UAS) is disclosed. In embodiments, the adaptive extension includes front-end and back-end cognitive engines on either side of an extension of the C2 backhaul network to a remote control station otherwise without a point of presence (PoP). Both cognitive engines transmit test packets to the other to refine coding schemes for transmission of C2 packets across the extension based on received feedback about the transmission. When C2 packets are received from the backhaul network or remote control station, the cognitive engines select an optimal coding scheme based on packet size. The cognitive engine encodes the C2 packets based on the optimal coding scheme. When C2 packets are received from the other cognitive engine, the applicable coding schemes are identified and the C2 packets decoded accordingly.

TECHNICAL FIELD

The subject matter disclosed herein is directed generally to unmannedaircraft system (UAS) traffic management and more particularly toinfrastructure for handling command and control (C2) traffic between UASand ground control facilities.

BACKGROUND

Wireless infrastructure is deployed for connecting Unmanned AerialSystems (UAS) to ground towers to facilitate the flow of Command andControl (C2) traffic. The waveforms deployed for this UAS C2infrastructure are point to multi-point waveforms (e.g., control andnon-payload communications (CNPC)) where the control towers serve asfocal points for the UAS C2 wireless segments. For example, a UASequipped with CNPC-waveform radio operating within the area of coverageof a control tower can maintain wireless communications to that controltower for both uplink and downlink C2 traffic. A UAS can switch over toa different control tower during its flight, e.g., if it travels into anew coverage area served by the different control tower. UAS flightpaths are preplanned, and a given flight plan will show which controltowers may be used for wireless access during which segments for theduration of the flight.

A deployed UAS C2 wireless infrastructure requires a ground backhaulnetwork to connect the control towers together, and to connect thecontrol towers to all control station locations where remote pilotscontrol UAS operations. For example, a complete UAS infrastructure has awireless segment through the UAS C2 waveform and a wired groundnetworking segment for backhauling UAS C2 traffic between remote controlstations and control towers. The combined wireless and wired (e.g.,physical) segments provide a complete infrastructure for seamless UASoperations. However, some control towers or control station locationsmay not have a point of presence (PoP) for the C2 backhaul network. TheC2 backhaul network must therefore be extended to these remotelocations.

The UAS C2 backhaul network may be extended to remote locations by avariety of means. Not all communications links are suitable for allbackhaul network extensions, however; for example, satellitecommunications (SATCOM) links may involve propagation delay incompatiblewith quality of service (QoS) requirements of the backhaul network.Similarly, retransmission of C2 traffic may not be a viable option inlight of QoS requirements. For example, transport protocols that rely onretransmission of lost packets may not be feasible because of the lowdelay requirements of some UAS C2 traffic. With respect to a C2 backhaulextension, UAS C2 traffic would go through the wireless segment, thewired backhaul network segment, and the extension segment. Even ifretransmission of lost packets can be configured to meet QoS delayrequirements with respect to the wireless and backhaul segments only,there is no guarantee that retransmission will meet delay requirementsthrough the additional extension segment. Accordingly, backhaul networkextensions should avoid retransmission due to the deleterious effect onend-to-end delay requirements.

SUMMARY

An adaptive extension apparatus for an unmanned aircraft system (UAS)command and control (C2) backhaul network is disclosed. In embodiments,the adaptive extension apparatus includes front-end and back-endcognitive engines on either side of the backhaul network extension, onecognitive engine in communication with the backhaul network itself andthe other cognitive engine in communication with the remote controlstation to which the backhaul network is extended. The front-end andback-end cognitive engines may be connected by a variety ofcommunications links. Each cognitive engine (e.g., the front-end to theback-end and the back-end to the front-end) transmits test or trainingpackets over the network extension to the other cognitive engine, whichgenerates performance feedback for the transmission based on one or morequality of service (QoS) parameters. The performance feedback is sentback to the transmitting cognitive engine, which revises coding schemesand/or media characteristics for transmitting C2 traffic based on whatthe performance feedback indicates. When C2 messages arrive fortransmission across the backhaul network extension (e.g., from thebackhaul network or the ground control station) the front-end (orback-end) cognitive engine identifies a data type or packet size of theC2 messages and selects an optimal coding scheme based on the data typeof the C2 messages. The front-end cognitive engine encodes the C2messages according to the selected scheme and transmits the encodedmessages across the backhaul network extension to the back-end cognitiveengine.

In some embodiments, communications links across the backhaul networkextension include wireless links and wired/physical links.

In some embodiments, coding schemes include media characteristics forconfiguring the C2 messages into over-the-air media frames.

In some embodiments, coding schemes include packet-repetition codingschemes.

In some embodiments, coding schemes include sliding-window codingschemes.

In some embodiments, coding schemes include packet-erasure codingschemes.

In some embodiments, QoS parameters include packet-loss ratio and packetdelay.

An adaptive extension apparatus for an unmanned aircraft system (UAS)command and control (C2) backhaul network is also disclosed. Inembodiments, the adaptive extension apparatus includes front-end andback-end cognitive engines on either side of the backhaul networkextension, one cognitive engine in communication with the backhaulnetwork itself and the other cognitive engine in communication with theremote control station to which the backhaul network is extended. Thefront-end and back-end cognitive engines may be connected by a varietyof communications links. Each cognitive engine receives data packetsfrom the other cognitive engine (e.g., across the backhaul networkextension) and determines whether the received packets are test/trainingpackets or actual C2 message traffic. If the received packets aretraining packets, the cognitive engine measures the performance of thepacket transmission according to one or more quality of service (QoS)parameters. The determined performance feedback is sent back across thenetwork extension to the transmitting cognitive engine. If the receivedpackets are C2 message traffic, the cognitive engine identifies theunderlying coding scheme used to encode the received packets and decodesthe C2 messages accordingly.

In some embodiments, communications links across the backhaul networkextension include wireless links and wired/physical links.

In some embodiments, coding schemes include packet-repetition codingschemes.

In some embodiments, coding schemes include sliding-window codingschemes.

In some embodiments, coding schemes include packet-erasure codingschemes.

In some embodiments, QoS parameters include packet-loss ratio and packetdelay.

A method for adaptive extension of an unmanned aircraft system (UAS)command and control (C2) backhaul network is also disclosed. Inembodiments, the method includes transmitting, via a front-end cognitiveengine, test or training data packets to a back-end cognitive engineacross a backhaul network extension. The method includes receivingperformance feedback about the transmitting from the back-end cognitiveengine. The method includes adjusting coding schemes for thetransmission of C2 message traffic based on the performance feedback.The method includes receiving C2 messages for transmission across thebackhaul network extension. The method includes identifying a data typeor packet size associated with the C2 messages. The method includesselecting an optimal coding scheme based on the C2 messages. The methodincludes encoding the C2 messages into one or more over-the-air messageframes based on the selected coding scheme. The method includestransmitting the encoded media frames across the backhaul networkextension to the back-end cognitive engine.

This Summary is provided solely as an introduction to subject matterthat is fully described in the Detailed Description and Drawings. TheSummary should not be considered to describe essential features nor beused to determine the scope of the Claims. Moreover, it is to beunderstood that both the foregoing Summary and the following DetailedDescription are example and explanatory only and are not necessarilyrestrictive of the subject matter claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures. The use of the same reference numbers in different instances inthe description and the figures may indicate similar or identical items.Various embodiments or examples (“examples”) of the present disclosureare disclosed in the following detailed description and the accompanyingdrawings. The drawings are not necessarily to scale. In general,operations of disclosed processes may be performed in an arbitraryorder, unless otherwise provided in the claims. In the drawings:

FIG. 1 is a block diagram illustrating an adaptive command and control(C2) backhaul network extension for unmanned aircraft systems (UAS)according to example embodiments of this disclosure;

FIG. 2 is a block diagram illustrating operations of the adaptive C2backhaul network extension of FIG. 1;

FIG. 3 is a block diagram illustrating coding schemes of the adaptive C2backhaul network extension of FIG. 1;

FIG. 4 is a block diagram illustrating coding schemes of the adaptive C2backhaul network extension of FIG. 1;

and FIGS. 5A and 5B are flow diagrams illustrating a method for adaptiveextension of a C2 backhaul network respectively for packet transmissionand packet reception according to example embodiments of thisdisclosure.

DETAILED DESCRIPTION

Before explaining one or more embodiments of the disclosure in detail,it is to be understood that the embodiments are not limited in theirapplication to the details of construction and the arrangement of thecomponents or steps or methodologies set forth in the followingdescription or illustrated in the drawings. In the following detaileddescription of embodiments, numerous specific details may be set forthin order to provide a more thorough understanding of the disclosure.However, it will be apparent to one of ordinary skill in the art havingthe benefit of the instant disclosure that the embodiments disclosedherein may be practiced without some of these specific details. In otherinstances, well-known features may not be described in detail to avoidunnecessarily complicating the instant disclosure.

As used herein a letter following a reference numeral is intended toreference an embodiment of the feature or element that may be similar,but not necessarily identical, to a previously described element orfeature bearing the same reference numeral (e.g., 1, 1 a, 1 b). Suchshorthand notations are used for purposes of convenience only and shouldnot be construed to limit the disclosure in any way unless expresslystated to the contrary.

Further, unless expressly stated to the contrary, “or” refers to aninclusive or and not to an exclusive or. For example, a condition A or Bis satisfied by any one of the following: A is true (or present) and Bis false (or not present), A is false (or not present) and B is true (orpresent), and both A and B are true (or present).

In addition, use of “a” or “an” may be employed to describe elements andcomponents of embodiments disclosed herein. This is done merely forconvenience and “a” and “an” are intended to include “one” or “at leastone,” and the singular also includes the plural unless it is obviousthat it is meant otherwise.

Finally, as used herein any reference to “one embodiment” or “someembodiments” means that a particular element, feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment disclosed herein. The appearances of thephrase “in some embodiments” in various places in the specification arenot necessarily all referring to the same embodiment, and embodimentsmay include one or more of the features expressly described orinherently present herein, or any combination or sub-combination of twoor more such features, along with any other features which may notnecessarily be expressly described or inherently present in the instantdisclosure.

Broadly speaking, embodiments of the inventive concepts disclosed hereinare directed to an apparatus and method for adaptive extension of acommand and control (C2) backhaul network for unmanned aircraft systems(UAS) to remote control locations without a point of presence (PoP). Theapparatus ensures all C2 traffic meets latency and reliabilityrequirements for UAS operations by adapting network encoding to incomingC2 traffic as it arrives. Adaptive encoding can identify and react toconnectivity issues within the network extension, adapting to ensurethat C2 traffic flow to the remote control locations meets the necessaryquality of service (QoS) without the need for retransmission of C2messages.

As C2 traffic across the backhaul network extension tends to berelatively low volume, it is possible to trade bandwidth for robustness.The resulting system redundancy ensures reliable transmission across thenetwork extension without the added delay caused by retransmission. Forexample, larger C2 packets may be fragmented into smaller transmissionframes and, through careful coding scheme selection, the probability oflosing such a large packet in transmission significantly reduced.

Referring to FIG. 1, a command and control (C2) environment 100 forunmanned aircraft systems (UAS) is disclosed. The C2 environment 100 mayinclude a C2 backhaul network 102 and points of presence 104 (PoP)connecting the C2 backhaul network to C2 enclaves 106.

In embodiments, some C2 enclaves 106 may include one or more controltowers forming a wireless local area network (LAN) while other C2enclaves may include control stations only; still other C2 enclaves maycombine LANs and control stations. For example, each control tower maymanage C2 traffic to and from UAS operating in its coverage area, whilecontrol stations may be associated with remote operators of individualUAS.

In embodiments, each PoP 104 may include a gateway router 108 bridgingthe C2 backhaul network 102 (e.g., a wide area network (WAN)) and theLANs of the C2 enclave 106. For example, the gateway router 108 mayincorporate border gateway protocol (BGP) and other like protocols toseparate LAN addresses associated with UAS C2 traffic from WAN addressesassociated with the C2 backhaul network 102. Further, the gateway router108 may establish internet protocol security (IPSec) tunnels through theC2 backhaul network 102 to ensure the security of C2 traffic. Stillfurther, the gateway routers 108 may map type of service (ToS) valuesfrom the C2 backhaul network 102 to UAS C2 traffic priority types.

In embodiments, the C2 backhaul network 102 may be configured to meetquality of service (QoS) requirements for UAS C2 traffic. For example,C2 traffic transmitted through the C2 backhaul network 102 may berequired to meet particular QoS parameters for latency, delay, or packetloss rates regardless of conditions throughout the network.

In embodiments, the remote C2 enclave 110 may be implemented and mayfunction similarly to the C2 enclave 106, except that the remote C2enclave 110 may be sufficiently remote from a PoP 104 as to require abackhaul network extension 112. For example, the backhaul networkextension 112 may provide one or more diverse means for extending the C2backhaul network 102 to the remote C2 enclave 110 via a gateway router108. For example, the remote C2 enclave 110 may include a mobile controlstation, and the backhaul network extension 112 may incorporate orleverage a public cellular wireless network as a means of extension.Other means of extension may include, but are not limited to, microwavelinks, public Internet, public cellular provider networks, and otherlike wired or wireless communication links 114.

In embodiments, the backhaul network extension 112 may incorporate anadaptive extension 116 to ensure that any UAS C2 traffic transmittedacross the backhaul network extension meets any applicable QoSrequirements. For example, the adaptive extension 116 may include afront-end cognitive engine 118 and a back-end cognitive engine 120 oneither end of the backhaul network extension 112. It should be notedthat UAS C2 traffic is bidirectional, so the front-end and back-endcognitive engines 118, 120 may create an adaptive closed-loop feedbackmechanism for bidirectional traffic, e.g., with respect to C2 trafficinbound to the C2 backhaul network 102 from the remote C2 enclave 110,and vice versa. The front-end and back-end cognitive engines may beimplemented as one or more software-based applications configured toexecute on one or more processors. In some embodiments, the front-end orback-end cognitive engines 118, 120 may report performance data anddynamic spectrum analysis information to a centralized server 122 fordisplay to, and analysis by, a human in the loop 124 (HITL). Forexample, based on performance data presented to the HITL 124, the HITLmay, through the centralized server 122, provide control input to thefront-end or back-end cognitive engines 118, 120, e.g., in order totrain the front-end and back-end cognitive engines the best mode ofautomatic reaction to a particular set of circumstances.

In embodiments, the front-end cognitive engine 118 may, when notactually transmitting C2 traffic across the C2 backhaul extension 112 tothe back-end cognitive engine 120, transmit test or training packets tothe back-end cognitive engine to learn about optimal network codingstrategies and media configurations based on different data types orlink conditions associated with the communications links 114. Forexample, the back-end cognitive engine 120 may receive the transmittedtest or training packets, providing the front-end cognitive engine 118with performance reports (126; e.g., performance feedback) as to thesuccess of the encoding or transmission (e.g., compared to applicableQoS requirements for C2 traffic). Based on this feedback, the front-endcognitive engine 118 may further adapt its stored encoding schemes(e.g., stored to memory or the like) to increase or decrease the degreeof error correction redundancy.

In some embodiments, the front-end cognitive engine 118 may respond to aperformance report by switching communications links 114, e.g.,switching the transmission of encoded data packets or test packets to anew or different communications link through the C2 backhaul extension112, e.g., a link associated with more favorable media characteristicsand/or better performance.

Referring now to FIG. 2, the adaptive extension 116 is shown.

In embodiments, the front-end and back-end cognitive engines 118, 120may be implemented as IP-layer software modules configured to execute onone or more processors. For example, the front-end and back-endcognitive engines 118, 120 may be programmed with, or may have access to(e.g., via memory 202 or other like data storage), configurationparameters and performance metric thresholds (e.g., delay, packet loss)for the C2 backhaul network 102. The back-end cognitive engine 120 maymeasure the performance of test or training packets 204 transmitted bythe front-end cognitive engine 118 across the backhaul network extension112 against these thresholds in order to provide performance reports 126to the front-end cognitive engine, which in turn may further adaptnetwork coding schemes for C2 traffic 204 a. For example, UAS C2 packetloss requirements may provide for a maximum tolerated packet loss ratioof 10⁻⁴ (e.g., 1 in 10,000) or less. If observed packet loss is higherthan 10⁻⁴, the front-end cognitive engine (based on performance reports126 generated and transmitted across the backhaul network extension 112by the back-end cognitive engine) may further refine network coding toincrease robustness and decrease packet loss. Similarly, if transmissionof the test or training packets 204 is associated with delay variation(e.g., jitter) that increases delay above a threshold level, thefront-end cognitive engine 118 may adapt network coding to reducejitter.

In embodiments, the front-end cognitive engine 118 may first attempt toidentify an optimum packet size for transmitting UAS C2 traffic 206(e.g., extension media) across the backhaul network extension 112. Forexample, UAS C2 traffic/extension media 206 may be associated with avariety of packet sizes and/or media characteristics associated with theconfiguration of C2 traffic message packets into IP message frames fortransmission across the backhaul network extension 112, including, e.g.,small messages compatible with a single over-the-air frame and largermessages that may require fragmentation to match the over-the-air framesize. In embodiments, the front-end cognitive engine 118 may firstdetermine the data type (e.g., packet size) of the extension media 206and select an optimum coding scheme and/or media characteristic based onthe identified packet size. For example, if the extension media 206consists of 3G wireless cellular media, the front-end cognitive engine118 may optimally map the packet size to a known 3G over-the-airtransmission frame size, e.g., matching a single IP packet to a singleover-the-air frame. Most extension media types are associated with avoice-over-IP (VoIP) type whereby a single short voice packet is mappedto a single over-the-air frame. In many cases, the front-end cognitiveengine 118 may map extension media 206 to its corresponding VoIP type(e.g., 20 bytes of payload to match wireless media VoIP codec G.729),which is generally the most suitable mapping for transmission across thebackhaul network extension 112, e.g., as the VoIP type may mosteffectively compensate for packet loss and may be associated with theleast delay. In some embodiments, as described above, a large C2 trafficmessage 206 (e.g., approaching 1 kB) may be fragmented into much smallertransmission frames, e.g., 50 frames of 20 bytes each.

In embodiments, the front-end cognitive engine 118 may select an optimumcoding scheme and/or media frame size (e.g., the frame size and/orcoding scheme resulting in minimal delay and/or minimal packet loss)based on the transmission performance of test packets of various sizesas measured by the back-end cognitive engine 120, and as communicatedback to the front-end cognitive engine 118 in the form of performancereports 126. To emphasize the importance of optimal packet size, itshould be noted that fragmentation of an IP packet into multipleover-the-air frames may increase packet loss ratio, as the loss of asingle frame (of N frames, where N is an integer) may result in the lossof the entire IP packet. For example, a C2 message 206 fragmented into10 over-the-air frames (where over-the-air frame loss ratio is in therange of 10⁻⁴, may result in IP packet loss in the 10⁻³ range. Further,fragmentation increases IP packet delay because the receiving end mustwait for all the frames of a given IP packet to arrive beforereassembling the packet.

In some embodiments, longer C2 messages 206 may be segmented and mappedto erasure coding (e.g., a ˜1 kB C2 message may be fragmented into 50frames of 20 kB each and frames repeated such that 60 or 70 such framesare actually transmitted, decreasing the probability that the loss ofany one component frame leads to the loss of the entire C2 message. Insome embodiments, shorter C2 messages 206 that arrive at a low rate maybe encoded according to packet repetition, e.g., one C2 message may bemapped to one extension packet regardless of the packet size in order tomeet QoS latency requirements.

In embodiments, the front-end cognitive engine 118 may map shorter,bursty messages to a packet-concatenation scheme (see, e.g., FIG. 3below) while short, infrequent messages may be mapped to apacket-repetition scheme. In some embodiments, the front-end cognitiveengine 118 may adapt the packet-repetition scheme by repeating one ormore frames of an encoded C2 message 206 additional times (206 a-c). Thereceived C2 packets 206 a-c may be decoded by the back-end cognitiveengine 120 into their component extension media 206 (e.g., after theback-end cognitive engine has identified the coding scheme used) andtransmitted to the C2 enclave (110, FIG. 1), e.g., via a gateway router(108, FIG. 1) connecting the adaptive extension 116 and the C2 enclave110.

In some embodiments, the front-end and back-end cognitive engines may betrained or supplemented by a human in the loop 208 (HITL). For example,performance reports 126 may be transmitted to the HITL 208 via acentralized server for analysis. Based on control input submitted by theHITL 208 through the centralized server, the front-end and back-endcognitive engines 118, 120 may build a larger knowledge base as to whichcoding schemes and/or media characteristics are best suited to a varietyof data types and/or link conditions.

Referring to FIG. 3, the adaptive extension 116 is shown.

In embodiments, the front-end cognitive engine 118 may, based onidentified media characteristics of extension media (e.g., UAS C2messages 302-312), concatenate multiple C2 short messages into a largemedia frame 314. For example, the UAS C2 messages 302-312 may each besmall in size, but may arrive at a relatively high rate or in bursts(compare, e.g., the short but non-bursty C2 messages incorporated intorepeated C2 packets 206 a-c above in FIG. 2). For example, the mediaframe 314 may include the UAS C2 messages 302, 304, 306, and 308. Thenext media frames 316, 318 transmitted by the front-end cognitive engine118 may respectively include the UAS C2 messages 304, 306, 308, and 310and 306, 308, 310, and 312. Accordingly, if the media frame 314including the UAS C2 message 306 is lost, the UAS C2 message 306 maystill be recovered from the media frames 316, 318. For any media frame314-318 incorporating N UAS C2 messages, N consecutive media frames mustbe lost for a single UAS C2 message 302-312 to be lost. Further, thesliding-window coding scheme may reduce jitter, as any excessivelydelayed or out of order media frames 314-318 may be discarded, and theircomponent UAS C2 messages 302-312 recovered by the back-end cognitiveengine (120, FIG. 2) from prior media frames already received. Asopposed to the large C2 message and small extension media frame sizesdiscussed above, sliding-window coding may provide a more robust codingscheme for smaller C2 messages 302-312 and a larger media frame 314-318.

In embodiments, the front-end cognitive engine 118 may adaptsliding-window coding by increasing or decreasing the number of UAS C2messages 302-312 incorporated within each media frame 314-318. Forexample, highly reliable media may be transmitted via media framesincluding a single UAS C2 message; similarly, as media reliabilitydecreases the number of UAS C2 messages 302-312 incorporated into eachmedia packet 314-318 may increase. Further, if media reliability is highbut subject to fluctuation, and bandwidth is sufficient to allow forlarger media frame sizes, sliding-window coding may provide foradditional system redundancy at negligible or zero cost.

Referring to FIG. 4, the adaptive extension 116 is shown.

In embodiments, the adaptive extension 116 may incorporatepacket-erasure coding for transmission of media frames 402, 404 acrossthe C2 backhaul network extension (112, FIG. 2). For example, the shortburst of C2 messages 302-312 shown above in FIG. 3 may be mapped into amedia frame 402 incorporating erasure coding without fragmentation.

In some embodiments, a large C2 message 406 may be received by thefront-end cognitive engine 118, which may opt to transmit the C2 messagevia erasure coding incorporating fragmentation of the large message intoK individual packets (e.g., where K is an integer). For example, thelarge C2 message 406 may be −1 kB, which the front-end cognitive engine118 may fragment into 50 packets 406 a, 406 b, . . . 406 k of −20 byteseach.

In embodiments, the front-end cognitive engine 118 may map the K UAS C2packets 406 a, 406 b, . . . 406 k into a media frame (404) incorporatingN encoded packets 404 a, 404 b, . . . 404 n (e.g., where K<N). Forexample, the front-end cognitive engine 118 may incorporate low-densityparity-check erasure coding or any like applicable erasure coding schemeor schemes.

In embodiments, the N encoded packets 404 a-k may include (N−K)redundancy packets 404 g-n (e.g., N=70, K=50::N−K=20). Generally,erasure coding may compensate for packet loss to an extent. For example,the back-end cognitive engine (120, FIG. 2) may reconstruct the K UAS C2packets 406 a-k based on any received K of the N transmitted encodedpackets 404 a-n. Similarly, erasure coding may compensate for jitter asan excessively delayed test packet or a packet received out of sequencemay be given up for lost, as its content may be recovered from theredundancy packets 404 g-n.

In some embodiments, the front-end cognitive engine 118 may compensatefor high packet loss by increasing N and thus N−K, or the number ofredundancy packets 404 g-n transmitted. Similarly, N−K may be decreasedwith respect to high media reliability.

FIGS. 5A/B—Method

Referring now to FIG. 5A, the method 500 may be implemented by theadaptive extension 116, and may include the following steps.

At a step 502, if there is currently no C2 traffic to transmit acrossthe backhaul network extension, the front-end cognitive engine generatestest or training packets for transmission across the variouscommunications links to the back-end cognitive engine.

At a step 504, the front-end cognitive engine receives performancefeedback from the back-end cognitive engine, the feedback indicating theperformance of the transmission of the test or training packets againstvarious quality of service (QoS) parameters, e.g., packet loss or delay.

At a step 506, the front-end cognitive engine adjusts its library ofcoding schemes based on the received performance feedback. For example,the front-end cognitive engine may refine packet sizes or mediacharacteristics corresponding to how a given C2 message to betransmitted is configured into over-the-air media frames.

At a step 508, C2 messages or traffic are received (e.g., from the C2backhaul network or from a remote ground station) for transmissionacross the backhaul network extension to the back-end cognitive engine.

At a step 510, the front-end cognitive engine identifies data typesand/or packet sizes associated with the received C2 messages.

At a step 512, the front-end cognitive engine selects an optimal codingscheme for transmission based on the identified data type.

At a step 514, the front-end cognitive engine encodes the C2 messagesinto over-the-air media frames according to the selected coding schemeand/or media characteristics.

At a step 516, the front-end cognitive engine transmits the encodedmedia frames across the backhaul network extension to the back-endcognitive engine.

Referring also to FIG. 5B, the method 500 may include additional steps518 through 528. At the step 518, the front-end cognitive enginereceives packets transmitted over the backhaul network extension by theback-end cognitive engine.

At a step 520, the front-end cognitive engine determines if the receivedpackets are test/training packets or C2 packets corresponding to a C2message.

At a step 522, if the received packets are test/training packets, thefront-end cognitive engine determines performance parameterscorresponding to the transmission and reception of the test/trainingpackets based on observed packet loss, delay, or other QoS parameters.

At a step 524, the front-end cognitive engine transmits the QoSperformance reports to the back-end cognitive engine through thebackhaul network extension.

At a step 526, if the received packets are C2 packets or media frames,the front-end cognitive engine identifies the coding scheme or schemesused to encode the C2 packets.

At the step 528, the front-end cognitive engine decodes the received C2packets according to the identified coding scheme.

CONCLUSION

It is to be understood that embodiments of the methods disclosed hereinmay include one or more of the steps described herein. Further, suchsteps may be carried out in any desired order and two or more of thesteps may be carried out simultaneously with one another. Two or more ofthe steps disclosed herein may be combined in a single step, and in someembodiments, one or more of the steps may be carried out as two or moresub-steps. Further, other steps or sub-steps may be carried in additionto, or as substitutes to one or more of the steps disclosed herein.

Although inventive concepts have been described with reference to theembodiments illustrated in the attached drawing figures, equivalents maybe employed and substitutions made herein without departing from thescope of the claims. Components illustrated and described herein aremerely examples of a system/device and components that may be used toimplement embodiments of the inventive concepts and may be replaced withother devices and components without departing from the scope of theclaims. Furthermore, any dimensions, degrees, and/or numerical rangesprovided herein are to be understood as non-limiting examples unlessotherwise specified in the claims.

We claim:
 1. An adaptive extension apparatus for an unmanned aircraftsystem (UAS) command and control (C2) backhaul network, comprising: atleast two cognitive engines including a front-end cognitive engine and aback-end cognitive engine communicatively connected by one or morecommunications links, the front-end cognitive engine communicativelycoupled to one of, and the back-end cognitive engine communicativelycoupled to the other of, 1) a UAS C2 backhaul network and 2) a UAS C2remote ground station not otherwise connected to the UAS C2 backhaulnetwork, the UAS C2 backhaul network associated with one or more qualityof service (QoS) parameters; each cognitive engine configured to:transmit one or more test packets to the other cognitive engine via theone or more communications links; receive feedback based on thetransmitting from the other cognitive engine via the one or morecommunications links, the feedback associated with the one or more QoSparameters; based on the received feedback, adjust one or more of acoding scheme and a media characteristic associated with thetransmission of one or more C2 packets via the one or morecommunications links; receive the one or more C2 packets from thebackhaul network or the remote ground station; identify at least onepacket size associated with the one or more C2 packets; select at leastone coding scheme based on the identified packet size; encode the one ormore C2 packets based on the selected coding scheme; and transmit theone or more encoded C2 packets to the other cognitive engine via the oneor more communications links.
 2. The adaptive extension apparatus ofclaim 1, wherein the one or more communications links include at leastone of a wireless link and a physical link.
 3. The adaptive extensionapparatus of claim 1, wherein the at least one coding scheme includes atleast one media characteristic associated with configuring the one ormore C2 packets into at least one message frame.
 4. The adaptiveextension apparatus of claim 1, wherein the at least one coding schemeincludes at least one packet repetition coding scheme.
 5. The adaptiveextension apparatus of claim 1, wherein the at least one coding schemeincludes at least one sliding window coding scheme.
 6. The adaptiveextension apparatus of claim 1, wherein the at least one coding schemeincludes at least one packet erasure coding scheme.
 7. The adaptiveextension apparatus of claim 1, wherein the one or more QoS parametersinclude at least one of a packet loss ratio and a packet delay.
 8. Anadaptive extension apparatus for an unmanned aircraft system (UAS)command and control (C2) backhaul network, comprising: at least twocognitive engines including a front-end cognitive engine and a back-endcognitive engine communicatively connected by one or more communicationslinks, the front-end cognitive engine communicatively coupled to one of,and the back-end cognitive engine communicatively coupled to the otherof, 1) a UAS C2 backhaul network and 2) a UAS C2 remote ground stationnot otherwise connected to the UAS C2 backhaul network, the UAS C2backhaul network associated with one or more quality of service (QoS)parameters; each cognitive engine configured to: receive one or morepackets from the other cognitive engine; determine whether the one ormore packets are test packets or C2 packets; if the one or more packetsare test packets: determine one or more QoS parameters corresponding tothe reception of the one or more packets; and transmit the one or moredetermined QoS parameters to the other cognitive engine via the one ormore communications links; and if the one or more packets are C2packets: identify the at least one coding scheme corresponding to theone or more packets; and decode the one or more packets according to theat least one identified coding scheme.
 9. The adaptive extensionapparatus of claim 8, wherein the one or more communications linksinclude at least one of a wireless link and a physical link.
 10. Theadaptive extension apparatus of claim 8, wherein the at least one codingscheme includes at least one packet repetition coding scheme.
 11. Theadaptive extension apparatus of claim 8, wherein the at least one codingscheme includes at least one sliding window coding scheme.
 12. Theadaptive extension apparatus of claim 8, wherein the at least one codingscheme includes at least one packet erasure coding scheme.
 13. Theadaptive extension apparatus of claim 8, wherein the one or more QoSparameters include at least one of a packet loss ratio and a packetdelay.
 14. A method for adaptive extension of an unmanned aircraftsystem (UAS) command and control (C2) backhaul network, the methodcomprising: transmitting, via a front-end cognitive engine, one or moretest packets to a back-end cognitive engine via one or morecommunications links across a backhaul network extension; receivingfeedback based on the transmitting from the back-end cognitive enginevia the one or more communications links, the feedback associated withone or more quality of service (QoS) parameters; based on the receivedfeedback, adjusting at least one coding scheme associated with thetransmission of one or more C2 packets via the one or morecommunications links; receiving the one or more C2 packets from at leastone of a backhaul network and a remote ground station; identifying atleast one packet size associated with the one or more C2 packets;selecting at least one coding scheme based on the identified packetsize; encoding the one or more C2 packets based on the selected codingscheme; and transmitting the one or more encoded C2 packets to theback-end cognitive engine via the one or more communications links. 15.The method of claim 14, wherein the one or more test packets are firsttest packets, the one or more C2 packets are first C2 packets, and themethod further comprises: receiving one or more packets from theback-end cognitive engine; determining whether the one or more secondpackets are second test packets or second C2 packets; if the one or morepackets are second test packets, 1) determining one or more QoSparameters corresponding to the reception of the one or more packets and2) transmitting the one or more determined QoS parameters to theback-end cognitive engine via the one or more communications links; and,if the one or more packets are second C2 packets, 1) identifying the atleast one coding scheme corresponding to the one or more packets and 2)decoding the one or more packets according to the at least oneidentified coding scheme.